5b0a6c7bc1
- 创建新的目录结构：research/、tools/（含子目录）和apps/ - 移动核心理论文件到research/core-theory/ - 移动天山理论文件到research/specialized/ - 重组tools/目录为多个子目录：content-generation/、data-processing/等 - 更新所有文档中的路径引用，包括README.md、项目结构说明.md等 - 更新工作流文件和脚本中的路径引用 - 更新文档索引文件中的路径引用
120 lines
3.7 KiB
Python
120 lines
3.7 KiB
Python
#!/usr/bin/env python3
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"""
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测试Milvus GPU配置的脚本
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"""
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import sys
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import os
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def test_gpu_availability():
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"""测试GPU可用性"""
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print("=== GPU可用性测试 ===")
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# 测试PyTorch CUDA
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try:
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import torch
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print(f"PyTorch版本: {torch.__version__}")
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print(f"CUDA可用: {torch.cuda.is_available()}")
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if torch.cuda.is_available():
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print(f"CUDA设备数量: {torch.cuda.device_count()}")
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print(f"设备名称: {torch.cuda.get_device_name(0)}")
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print(f"CUDA版本: {torch.version.cuda}")
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return True
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else:
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print("CUDA不可用")
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return False
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except Exception as e:
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print(f"PyTorch测试失败: {e}")
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return False
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def test_milvus_connection():
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"""测试Milvus连接"""
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print("\n=== Milvus连接测试 ===")
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try:
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from pymilvus import connections, utility
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print("PyMilvus导入成功")
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# 尝试连接本地Milvus
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try:
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connections.connect("default", host="localhost", port="19530")
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print("Milvus连接成功")
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# 检查Milvus版本
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version = utility.get_server_version()
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print(f"Milvus版本: {version}")
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return True
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except Exception as e:
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print(f"Milvus连接失败: {e}")
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print("注意: 这需要先启动Milvus服务")
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return False
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except Exception as e:
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print(f"PyMilvus导入失败: {e}")
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return False
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def test_gpu_memory():
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"""测试GPU内存"""
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print("\n=== GPU内存测试 ===")
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try:
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import torch
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if torch.cuda.is_available():
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# 获取GPU内存信息
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device = torch.cuda.current_device()
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total_memory = torch.cuda.get_device_properties(device).total_memory
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allocated_memory = torch.cuda.memory_allocated(device)
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cached_memory = torch.cuda.memory_reserved(device)
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print(f"GPU总内存: {total_memory / 1024**3:.2f} GB")
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print(f"已分配内存: {allocated_memory / 1024**3:.2f} GB")
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print(f"缓存内存: {cached_memory / 1024**3:.2f} GB")
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# 测试GPU计算
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print("\n=== GPU计算测试 ===")
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x = torch.randn(1000, 1000, device='cuda')
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y = torch.randn(1000, 1000, device='cuda')
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z = torch.mm(x, y)
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print("GPU矩阵乘法测试成功!")
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print(f"结果张量形状: {z.shape}")
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print(f"结果张量设备: {z.device}")
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return True
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else:
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print("CUDA不可用，无法测试GPU内存")
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return False
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except Exception as e:
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print(f"GPU内存测试失败: {e}")
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return False
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def main():
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print("Milvus GPU配置测试")
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print("=" * 50)
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# 测试GPU可用性
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gpu_available = test_gpu_availability()
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# 测试Milvus连接
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milvus_available = test_milvus_connection()
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# 测试GPU内存和计算
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gpu_memory_ok = False
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if gpu_available:
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gpu_memory_ok = test_gpu_memory()
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# 总结
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print("\n" + "=" * 50)
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print("测试总结:")
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print(f"GPU可用: {'✓' if gpu_available else '✗'}")
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print(f"Milvus连接: {'✓' if milvus_available else '✗'}")
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print(f"GPU计算: {'✓' if gpu_memory_ok else '✗'}")
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if gpu_available and gpu_memory_ok:
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print("\n🎉 GPU配置正常，可以用于Milvus等GPU加速应用!")
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else:
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print("\n⚠️ GPU配置存在问题，可能影响Milvus等应用的GPU加速功能")
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if __name__ == "__main__":
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main()
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